this document captures the working notes from the workshop ... · step 3. scope change by thinking...
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This document captures the working notes from the workshop "Workshop: Capability to acquire, create and manage the DATA in forms that
allow secure interoperability and integration", held at Churchill College Cambridge on 10-11 April 2018
The summary sheets are assembled from the separate working groups from each of two streams; Research and Applications.
The details of the outputs from the individual working groups are captured in turn.
This material was used as a starting point for the creation and development of the Capability Framework and the Research Landscape. It is
provided as source material for the interested reader.
Rank order Topic title
1 Data integration system
- How to build federated DB/integrate
- Meta data frameworks around quality
- Integration of real time w/static
- Breaking down boundaries around data
- Applicability
2How to manage Risk and Accountability
over lifetime
3Data DNA (7)
+
- Provenance - mixing of data
- Accuracy (true reflection)
4 Understanding data requirements- Applicability to other contexts
- AIR -> PIR (public info requirement)
5 Develop ontologies for DBB- Static and real-time, quant and qual
- Standards and protocols
6How to manage/incorporate new forms
of data w/existing structures
7 Handing legacy data - Capturing as-is, tacit info
Acquire, create and manage DATA - Research Summary
Scope out What sub-topics might overlap with other topics?
- Non-linear systems feedback
- Analytics /information modelling +
Governance + Complex systems
- NB archaeological data or data of past
environments as a special case
Articulate user needs and requirementsConceive, plan and design (including optimisation and
integration)
Build and commission (including optimisation and
integration)
Manage and Operate (refine and enhance, optimise
and integrate)
Provide valued services to users (and minimise
downsides for non-users)
Retrofit / Renew / Decommission (with attention to
the whole cycle)…Assess, feedback and optimisation
- Protocols
- Process- Feedback verification
Research Topic: …
Acquire, create and manage the Data
e.g. National/Regional
Step 3. Scope change by thinking about spatial differences
Step 2. Scope change by thinking about stakeholders
Scope:
e.g. City/local e.g. Asset specific
- Access to knowledge of state of place to aid decision to act
- (Archology) Pre-construction information for new design
- Trade-off between data detail / complexity and its purpose of use
Scope - In
- Cyber security for provenance
- Big data management
- Sensor optimisation location
- Metadata frameworks -->Bias
- Federated Data Architecture
- Data fusion
- Integrating real time with geometry + topology of the data flows --> temporal
dynamics
- Targeted sensing: When, where and how often?
- Performance metrics of data quality --> provenance
- Ontology for DBB: Quantitative, Qualitative and Subjective
- Flexible platform for data management for different sourced types of data
- Physical extents of built environment
- Second order effects
- Comparative capability relationships
- Understand cycle + verify source data sets
- Data and organisation change
Step 4. Scope change by thinking about the lifecycle of assets and services
- Infrastructure
Planning
Communication visualization trust
Mapping between scales:
Room --> building --> Neighbourhood -->City -->Region -->National
Scope out What sub-topics might overlap with other topics?
- Data schemas/Ontology e.g.
Uniclass for linear assets?
- Deliver vs. operate vs. integrate
- Data organisation and
interoperable potential
- Secure distributed data stores -
Block chain
- Sharing data between agencies:
> Data protections legislation
and permissions
> Reluctant sharers
- ownership
- Cost of capture, manage, usage
and preservation of data
- ££ for data collection + updating
data / data will become dated
- Excessive data (Oscar Wilde) -
Accumulated but unused
- Understanding data requirements
- less creativeness
- Selecting from huge quantities of
data - what is useful / required?
- Value--> information-->Sensor
data
- Ethics of storing data for so long?
- Data obsolescence over life-cycle
(identification and management)
- Currency (i.e. up-to-datedness) of
data
- What is the life cycle of BE in
question? How long do you collect
data for?
- Contextualization time sensitive
- Digital data preservation of
longer life-cycle
- Data uncertainties (identification,
quantification, visualization
management)
- Trust - Multiple sources of "truth"
- Hierarchies of data - what is
considered more important than
other data
- Ensuring we consider quantitative
data and the - more detailed (often
more time consuming + costly to
collect) qualitative data
- Data validation and verification
- Handling legacy data
- (H) BIM
> Sensed - to - BIM
> As-Is modelling
> Sensing the invisible
- Crowd sourcing in tagging (ranking)
data (usability, quantity)
Articulate user needs and requirementsConceive, plan and design (including
optimisation and integration)
Build and commission (including optimisation
and integration)
Indoor localization
Understand the ECOSYSTEM e.g. between Assets and systems (integration)
Linear + Non-Linear Assets
Research Topic: …
Scope:
Scope - In
…Assess, feedback and optimisation
Acquire, create and manage the Data
Manage and Operate (refine and enhance, optimise and integrate) Provide valued services to users (and minimise downsides for non-users) Retrofit / Renew / Decommission (with attention to the whole cycle)
Step 4. Scope change by thinking about the lifecycle of assets and services
e.g. Asset specific
Step 2. Scope change by thinking about stakeholders
Step 3. Scope change by thinking about spatial differences
e.g. National/Regional e.g. City/local
Translation between scales
Scope out
Block chain "myth"
Cost of getting each dataset vs. Cost of
handling data at volume
Articulate user needs and requirementsConceive, plan and design (including optimisation
and integration)
Build and commission (including optimisation and
integration)
Manage and Operate (refine and enhance, optimise
and integrate)
Provide valued services to users (and minimise
downsides for non-users)
Retrofit / Renew / Decommission (with attention to
the whole cycle)…Assess, feedback and optimisation
Developers and operators together:
stakeholders forumInformed end user to an informed client
Speculative developments and
guesswork in end user requirements
Research Topic: …
Acquire, create and manage the Data
Scope:
What sub-topics might overlap with other topics?Scope - In
- Contractual liability and contracts
- Permission and access level
- Information provenance (authenticity and quality)
- Ownership of information IP and copyright
- How to use data, not just store/manage?
- How to support data interoperability by distributing computation not data
- Hierarchical data acquisition and modelling
- Focus on data use
- Decentralized data sets
- Capture data once and use it many times over
- Access to data: Who and how much, controlling and access - Privacy
- Future proofing of data required as knowledge develops
- How to provide for accountability e.g. Provenance, instrumentation etc..?
"DEVOPS" for DBB?
(Procurement vs. Operation)
Consider dataset as an 'asset'
e.g. National/Regional
- How to handle the many stakeholders over 10-50 year lifespan of Assets --> Complexity
- How to construct contracts to resolve tension in use f digital Asset analogous to CAPEX vs. OPEX vs. TOTEX considerations
- Stakeholders change along the project life-cycle
- Data lifespan: Building lifecycle vs. Information lifecycle
- Different stakeholder priorities
- Legacy of the data
Step 4. Scope change by thinking about the lifecycle of assets and services
e.g. Asset specific
Step 2. Scope change by thinking about stakeholders
Step 3. Scope change by thinking about spatial differences
e.g. City/local
Scope out What sub-topics might overlap with other topics?
Crowdsourced data
Context dependency:- `Implications for
data storage in hospitals and transport
hub
Articulate user needs and requirementsConceive, plan and design (including optimisation
and integration)
Build and commission (including optimisation and
integration)
Manage and Operate (refine and enhance, optimise
and integrate)
Provide valued services to users (and minimise
downsides for non-users)
Retrofit / Renew / Decommission (with attention to
the whole cycle)…Assess, feedback and optimisation
Identify what data is required for
predictive maintenance
e.g. City/local
Research Topic: …
Acquire, create and manage the Data
Scope:
- Minimal + appropriate data collection to refine/add confidence in model of building
- International data schema
- Effective data collection and storage methods: CQR code, RFiD
- Data from building users e.g. wearables. Different implications to 'building generated' data
- How people use physical / digital space
- IP and data ownership:
> who owns the data?
> why is this a limitation?
- Identify new data sources for digital technologies (twins)
- New standards for data exchange
- Automation and accountability
- Move from file-based systems to data-repositories
- Sematic data and ontologies (relationship between entities networking)
Scope - In
e.g. Asset specific
Step 2. Scope change by thinking about stakeholders
- Policy makers incentivize stakeholders to share data
- Business model to support 'activities'
- Risk management in open data responsibility / data role
Step 3. Scope change by thinking about spatial differences
e.g. National/Regional
Identify what data is needed at every stage
- Cost benefit of raw data storage management? --> Data 'flood' of storing sensor
data even at a local level
- Multiple users of same data points --> Sharing : Purpose / Benefits
- Integration of different data sources
- Loss of data provenance along processing chain
- Increased likelihood of 'poor' data quality / completeness at scale --> inconsistent
- Amount of data to be recorded«- Policy handbook
- Data security
- Standards
Increasing sources of data as the Scale increases
Step 4. Scope change by thinking about the lifecycle of assets and services
What capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this?
- Ontology of DBB + Operationalise
ANAN (UCL)
ETH Zurich
OS
IDBE
National working group CDBB + IDBE
(Standards and Protocols)
How to develop platforms for data
integration
Data Fusion
How to extract information knowledge
for big data
ITRC / Mistral
↓
DAFNI
UKCRIC Observatories
- Federation DB
- Real time integration with static
Geometry / Topology
- Metadata frameworks: provenance,
linage, uncertainty, quality,
DAFNI
Security
Intra scale / inter scale capability
(spatial and temporal)
Organisation 'buy in'
Data evidenced infrastructure Bryden
Wood
CHSA
IDBE
Newcastle SAM
Research Topic
Acquire, create and manage the Data
What are capabilities and research that will be needed as DBB matures from ‘deliver’ to ‘operate’ to ‘integrate’?
Integrate (deliver services and benefits based on integrated systems and organisations)
Step 1. What are the major research
clusters/themes?
Operate (manage asset through life and deliver the services that derive from and depend on the asset)Deliver (create the built asset)
What capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this?
Developing / designing appropriate
SchemasLinear assets (Cross rail, HS2 etc..)
NBS
Building Smart
Linear assets (Cross rail, HS2 etc..) COBie people
Understanding data requirements +
cost of ownership
Data certainty and obsolescence- What are the factors (uncertainties)
- Can we visualise them?
Handling legacy dataAs-Is modelling --> invisible elements /
aspectsTacit Information --> Making explicit
Governance, Security and Access Unman factors (security)
- Lots of Block Chain for contracting
- "secured communications" + other
encrypted platforms
Block Chain
Data sharing:
> Voluntary/ involuntary
> Reluctant sharers
> Ethics
Develop meaningful E.I.R.s
(employment Information requirements)
Developing A.I.R.s
(Asset Information Requirements)Develop "Public information Requirements"
Research Topic
Acquire, create and manage the Data
Step 1. What are the major research
clusters/themes? What are capabilities and research that will be needed as DBB matures from ‘deliver’ to ‘operate’ to ‘integrate’?
Deliver (create the built asset) Operate (manage asset through life and deliver the services that derive from and depend on the asset) Integrate (deliver services and benefits based on integrated systems and organisations)
What capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this?
- Measures of data quality + use of
such in contract + liability
- Capture + provision of Metadata
- Data accuracy: is this a true reflection
of what's happening/ happened?
Digital virtual observatory: LIGO
Liability, Contract, Legislation needs +
implementation
- Provenance in / use of data / mixing
of data
- Search engine for data / information
Capturing user data e.g. Highways -
people not just traffic
Developing data detail:
> levels of information
> levels of structure
How to marry the structured, rigid,
well defined construction world with
fuzzy, uncontracted ICT/CS world?
- Open architectures for integrity sensor
data to BIM models
- Linking / assessing structured e.g. BIM
data and e.g. sensor data
Research Topic Delegate names
2A Acquire, create and manage the Data
Step 1. What are the major research
clusters/themes? What are capabilities and research that will be needed as DBB matures from ‘deliver’ to ‘operate’ to ‘integrate’?
Deliver (create the built asset) Operate (manage asset through life and deliver the services that derive from and depend on the asset) Integrate (deliver services and benefits based on integrated systems and organisations)
[Not stated]
What capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this? What extra capabilities and enabling research? Which people / institutions are working on this?
- Risk management
- IP and data ownership
- Accountability (liability, ownership,
regulation)
- How to manage risk and accountability
across the lifecycle of data and assets
- Smart contracts and legal Frameworks
- Awareness and ethical training
- Block chain
- Skills and knowledge
- Digital / Physical data sources
- How to manage and incorporate new forms
of data aligned with existing assets?
- Automation / Digital Twin: how to manage
new data? (including digital assets)
- Best practice of data management
- Integration of different new assets
and aligned with new assets
How to manage Quality + Quantity- New methodologies and tools
- Digital infrastructure standard
- Business models to support data activities
- What are the capabilities to build new data
driven business models from new data
sources?
- Identify the ECOSYSTEM players to
create data driven business models
- Institution knowledge
- Make the case of data as an asset
Horizon Digital Economy Nottingham University
Research Topic
2A Acquire, create and manage the Data
Step 1. What are the major research clusters/themes? What are capabilities and research that will be needed as DBB matures from ‘deliver’ to ‘operate’ to ‘integrate’?
Deliver (create the built asset) Operate (manage asset through life and deliver the services that derive from and depend on the asset) Integrate (deliver services and benefits based on integrated systems and organisations)
ATI
BSI
Building Smart - BRE
Big Data - Cambridge Service Alliance
BDAL - UWE
Cambridge Service Alliance
Challenge to differentiate given the complexity of the future system
Rank order Topic title
1 Data retrofitFinding out what we need to know about existing assets -
meaningfully/good enough…
2 Asset stock performance classification
- Peer comparison
- Dynamic
- e.g. can I charge my Tesla or will it be powering the office?
3Identification and management of assets across
different portfolios of ownership and responsibility
- ID
- Classification
- Discovery
- Breaking silos
4 Citizen as a Sensor (e.g.. for asset condition) Technical aspects: Data creation and acquisition
Governance: Privacy, "he who shouts loudest" etc
5Managing Borders post Brexit: oil, gas, power,
people, goods, shipping, smuggling- National integrated model of Access points and flows
6"Campus" or "District" level data store with
Graphical Prog Language - Citizen generated Apps
Acquire, create and manage DATA - Application/Demonstrators Summary
Scope out What sub-topics might overlap with other topics?
- Commercial models for information
exploitation
- Unintended uses of data…? e.g.
->security implications of 'merging'
data sets to gain access to gain new
insights
-> does this place any onus on the
supplier?
Articulate user needs and requirementsConceive, plan and design (including optimisation
and integration)
Build and commission (including optimisation and
integration)
Manage and Operate (refine and enhance, optimise
and integrate)
Provide valued services to users (and minimise
downsides for non-users)
Retrofit / Renew / Decommission (with attention to
the whole cycle)…Assess, feedback and optimisation
Service feedback from the users -->
feedback to the design
Step 4. Scope change by thinking about the lifecycle of assets and services: Are there new / different aspects of the topic and its demonstrators if we think through the lifecycle of the assets and the services?
Step 2. Scope change by thinking about stakeholders (Are there new / different aspects of the topic and its demonstrators?)
Step 3. Scope change by thinking about spatial differences (e.g. to consider how can scale make a difference to the demonstrators we would propose)
e.g. National/Regional e.g. City/local e.g. Asset specific
- Ladder of control across geographic scale
- Data accessibility
- Level of granularity of data
Government funders / user/ arbiter / legislator
Citizen (user)
- Asset owners
- Asset operators
- Financiers
- Data acquirers
- Insurers
- Regulators
- Data quality assessment
- Data models (for legislation) across broad scope
- Data collection - structured
- Sensitive information
- Ensuring data quality in challenging environments
- Interoperability
- Master reference data
- Automatic data collection (using drones)
- Integrated data stream
- Data quality --> frequency, management
- Sharability and security
- Data requirements --> how do you take a Broadview
- Measure value of the data to the end users --> cost allocation to fund capture?
- Ontologies
- Intentional as well as sensor data
- Funding model for data acquisition
- Data 'authority' ---> an accepted 'truth'
- Data granularity --> measure the individual
- M2M applications --> data for a 'new audience'
- Temporal agent --> now/real-time
Application Topic: …
Acquire, create and manage the Data
Step 1. Scope: What topics should we include in this part of the framework – and what demonstrators would illustrate / stretch the boundaries?
Scope - In
Scope out What sub-topics might overlap with other topics?
Is very old data out of scope? and if so
how old?Social media data and temporal info
- Cost
- Data gives performance
- Asset = where cost comes to get data
city/regional where benefit is realised
e.g. NON - ASSET related (data)
unit-less measure that includes:
> Latent heat
> Gravity
Articulate user needs and requirementsConceive, plan and design (including optimisation
and integration)
Build and commission (including optimisation and
integration)
Manage and Operate (refine and enhance, optimise
and integrate)
Provide valued services to users (and minimise
downsides for non-users)
Retrofit / Renew / Decommission (with attention to
the whole cycle)…Assess, feedback and optimisation
- Structured digital brief
- Operational performance data
requirements
Structure the involvement of O&M
teams to influence the design early on
i.e. GSL policy
Model & asset verification of Built
(data)How much cost to keep data updated?
Provide views / extracts for user needs
& level of detail
- Design life:
> fault history
> costs history
> performance analysis
- Deterioration modelling
Step 4. Scope change by thinking about the lifecycle of assets and services: Are there new / different aspects of the topic and its demonstrators if we think through the lifecycle of the assets and the services?
Step 2. Scope change by thinking about stakeholders (Are there new / different aspects of the topic and its demonstrators?)
Step 3. Scope change by thinking about spatial differences (e.g. to consider how can scale make a difference to the demonstrators we would propose)
e.g. National/Regional e.g. City/local e.g. Asset specific
-Better regulation and policy for decade long instructions
- Benefits --> TOTEX
- Better operational decisions
- Optimisation
- Different people - different needs
- Different data uses have different quality criteria
- Release data on user-based granularity
- How do different data base types communicate e.g. CityXML and IFC
- Specific view points for each user type - same data
- Proxies for data in existing buildings
- Define asset / services / performance
- Static data vs. Dynamic data -->How do we trust it?
- Differentiate: data / info / knowledge / vision
- Look at data standards from parallel industries
- Common language of data exchange IFC
- Units of measure should be part of data definitions
- Standards NOT PAS's
- Crowdsource of data: low quality, very accessible, cheap
- What is data quality?
- Granularity of information
- Acquisition of data vs. data transactions
- Common language for constructed assets
Application Topic: …
Acquire, create and manage the Data
Step 1. Scope: What topics should we include in this part of the framework – and what demonstrators would illustrate / stretch the boundaries?
Scope - In
What would be the big challenges? How? What would be the big challenges? How? What would be the big challenges? How?
Citizen as a monitor / sensor e.g. pot
hole identification
How to engage the citizen with the
process e.g. openstreetmap
Privacy issues:
> data sharing
> data granularity
> secondary data use (e.g. speeding!)
Different 'app' developers
Different down-stream users-->
consistent user requirement
HMG as an asset owner/operator in
different portfolio's management
regimes impact each other, but in an
unknown manner
Data integration
- Integration data model
- Data integration and sharing
environment
- Common master + reference data
- Data mapping into integration model /
REF data
Optimise running of asset classes
against widest set of objectives
Feedback gaps between asset
management teams --> upwards and
downwards
Feedback loop to 'design'
Managing post Brexit
- Construct National Infrastructure
Model e.g. Oil, Gas, Power, People,
Energy, Onshore, Offshore, Shipping,
Smuggling
- Model that integrates domains:
> on / off shore
> above / below ground
> indoor / outdoor
Data compilation process:
> sensed / captured
> aggregated / informed
Level of granularity need to be defined
for users
Rejuvenate the high street - using real-
time data to model + understand how
space is used
Application Topic
Acquire, create and manage the Data
Step 1. What are major demonstrators that are
required? What capabilities / functionalities of the demonstrators illustrate the maturing of DBB from ‘deliver’ to ‘operate’ to ‘integrate’?
Deliver (create the built asset) Operate (manage asset through life and deliver the services that derive from and depend on the asset) Integrate (deliver services and benefits based on integrated systems and organisations)
What would be the big challenges? How? What would be the big challenges? How? What would be the big challenges? How?
Data retrofit
(migration / mapping)
- Granularity required for meaningful
output
- Access to asset to gain data
- Classify & grading of sensor detail
required - is it worth it?
- Advanced auto survey techniques
Quality of data / cost to retrofitStandardised high level outputs as open
re-useable info
How to encourage take-up? (What's in
it for me?)
Open 'App" culture - sell access to API
on data
Operational
Asset stock performance classification
Asset classifications across
organisationsData standards
Performance capability vs. Actual
performance (behaviours driven?)
Open sources data on campus project
with API to write apps
Value & cost of data?
Security of data sharing IP
Proxies for non-available dataFeedback loop for continuous
improvement
Application Topic
Acquire, create and manage the Data
Step 1. What are major demonstrators that are
required? What capabilities / functionalities of the demonstrators illustrate the maturing of DBB from ‘deliver’ to ‘operate’ to ‘integrate’?
Deliver (create the built asset) Operate (manage asset through life and deliver the services that derive from and depend on the asset) Integrate (deliver services and benefits based on integrated systems and organisations)